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Reconfigurable intelligent surfaces (RISs) have attracted increasing interest from both academia and industry, thanks to their unique features on controlling electromagnetic (EM) waves. Although theoretical models for RIS-empowered…
We conjecture that hidden state vectors corresponding to individual input tokens encode information sufficient to accurately predict several tokens ahead. More concretely, in this paper we ask: Given a hidden (internal) representation of a…
The evolution toward sixth-generation wireless systems positions intelligence as a native network capability, fundamentally transforming the design of radio access networks (RANs). Within this vision, Semantic-native communication and…
The sixth generation (6G) targets ultra reliable, low latency (URLLC) gigabit connectivity in mmWave bands, where directional channels require precise beam alignment. Reconfigurable intelligent surfaces (RIS) reshape wave propagation and…
Reconfigurable intelligent surface (RIS)-empowered communication, has been considered widely as one of the revolutionary technologies for next generation networks. However, due to the novel propagation characteristics of RISs, underlying…
Future 6G radio access networks (RANs) will be artificial intelligence (AI)-native: observed, reasoned about, and re-configured by autonomous agents cooperating across the cloud-edge continuum. We introduce MX-AI, the first end-to-end…
State space models have shown to be effective at modeling long range dependencies, specially on sequence classification tasks. In this work we focus on autoregressive sequence modeling over English books, Github source code and ArXiv…
Reconfigurable Intelligent Surfaces (RIS) constitute a promising technology that could fulfill the extreme performance and capacity needs of the upcoming 6G wireless networks, by offering software-defined control over wireless propagation…
Quantum optimal control (QOC) provides a systematic framework for achieving high-fidelity operations in quantum systems and plays a central role in tasks such as gate synthesis, state transfer, and pulse design. Existing QOC methods broadly…
Open-Radio Access Network (O-RAN) has become an important paradigm for 5G and beyond radio access networks. This paper presents an xApp called xSlice for the Near-Real-Time (Near-RT) RAN Intelligent Controller (RIC) of 5G O-RANs. xSlice is…
The increasing complexity of Beyond 5G and 6G networks necessitates new paradigms for autonomy and assur- ance. Traditional O-RAN control loops rely heavily on RIC- based orchestration, which centralizes intelligence and exposes the system…
We consider a narrowband MIMO reconfigurable intelligent surface (RIS)-assisted wireless communication system and use tensor signal modelling techniques to individually estimate all communication channels including the non-RIS channels…
Recently, there has been a growing interest in Long-term Time Series Forecasting (LTSF), which involves predicting long-term future values by analyzing a large amount of historical time-series data to identify patterns and trends. There…
Dynamic spectrum access (DSA) has become a key pillar of next-generation wireless systems to address the spectrum scarcity due to the rapid growth of connected devices. Accurate short-term spectrum forecasting is critical for DSA, where…
We consider sequential state and parameter learning in state-space models with intractable state transition and observation processes. By exploiting low-rank tensor train (TT) decompositions, we propose new sequential learning methods for…
The O-RAN architecture is transforming cellular networks by adopting RAN softwarization and disaggregation concepts to enable data-driven monitoring and control of the network. Such management is enabled by RICs, which facilitate…
Artificial intelligence approaches for base-band processing for radio receivers have demonstrated significant performance gains. Most of the proposed methods are characterized by high compute and memory requirements, hindering their…
Reconfigurable intelligent surfaces (RISs) are envisioned as a key enabler for next-generation wireless networks, offering programmable control over propagation environments. While extensive research focuses on planar RIS architectures,…
Effectively learning from sequential data is a longstanding goal of Artificial Intelligence, especially in the case of long sequences. From the dawn of Machine Learning, several researchers have pursued algorithms and architectures capable…
The number of connected mobile devices and the amount of data traffic through these devices are expected to grow many-fold in future communication networks. To support the scale of this huge data traffic, more and more base stations and…